Stacking as a tool for studying objects that are not individually detected is becoming popular even for radio interferometric data, and will be widely used in the SKA era. Stacking is typically done using imaged data rather than directly using the visibilities (the uv-data). We have investigated and developed a novel algorithm to do stacking using the uv-data. We have performed exten- sive simulations comparing to image-stacking, and summarize the results of these simulations. Furthermore, we disuss the implications in light of the vast data volume produced by the SKA. Having access to the uv-stacked data provides a great advantage, as it allows the possibility to properly analyse the result with respect to calibration artifacts as well as source properties such as size. For SKA the main challenge lies in archiving the uv-data. For purposes of robust stacking analysis, it would be strongly desirable to either keep the calibrated uv-data at least in an aver- age form, or implement a stacking queue where stacking positions could be provided prior to the observations and the uv-stacking is done almost in real time.

Skapa referens, olika format (klipp och klistra)

BibTeX @conference{Knudsen2015,author={Knudsen, Kirsten Kraiberg and Lindroos, Lukas and Vlemmings, Wouter and Conway, John and Marti-Vidal, Ivan},title={Stacking of SKA data: comparing uv-plane and and image-plane stacking},booktitle={Proceedings of Advancing Astrophysics with the Square Kilometre Array (AASKA14)},abstract={Stacking as a tool for studying objects that are not individually detected is becoming popular even for radio interferometric data, and will be widely used in the SKA era. Stacking is typically done using imaged data rather than directly using the visibilities (the uv-data). We have investigated and developed a novel algorithm to do stacking using the uv-data. We have performed exten- sive simulations comparing to image-stacking, and summarize the results of these simulations. Furthermore, we disuss the implications in light of the vast data volume produced by the SKA. Having access to the uv-stacked data provides a great advantage, as it allows the possibility to properly analyse the result with respect to calibration artifacts as well as source properties such as size. For SKA the main challenge lies in archiving the uv-data. For purposes of robust stacking analysis, it would be strongly desirable to either keep the calibrated uv-data at least in an aver- age form, or implement a stacking queue where stacking positions could be provided prior to the observations and the uv-stacking is done almost in real time.},year={2015},}

RefWorks RT Conference ProceedingsSR ElectronicID 225695A1 Knudsen, Kirsten KraibergA1 Lindroos, LukasA1 Vlemmings, WouterA1 Conway, JohnA1 Marti-Vidal, IvanT1 Stacking of SKA data: comparing uv-plane and and image-plane stackingYR 2015T2 Proceedings of Advancing Astrophysics with the Square Kilometre Array (AASKA14)AB Stacking as a tool for studying objects that are not individually detected is becoming popular even for radio interferometric data, and will be widely used in the SKA era. Stacking is typically done using imaged data rather than directly using the visibilities (the uv-data). We have investigated and developed a novel algorithm to do stacking using the uv-data. We have performed exten- sive simulations comparing to image-stacking, and summarize the results of these simulations. Furthermore, we disuss the implications in light of the vast data volume produced by the SKA. Having access to the uv-stacked data provides a great advantage, as it allows the possibility to properly analyse the result with respect to calibration artifacts as well as source properties such as size. For SKA the main challenge lies in archiving the uv-data. For purposes of robust stacking analysis, it would be strongly desirable to either keep the calibrated uv-data at least in an aver- age form, or implement a stacking queue where stacking positions could be provided prior to the observations and the uv-stacking is done almost in real time.LA engLK http://pos.sissa.it/archive/conferences/215/168/AASKA14_168.pdfLK http://publications.lib.chalmers.se/records/fulltext/225695/local_225695.pdfOL 30